Emilio Cano Renteria ’23
Civil and Environmental Engineering
Detecting Growth Rings in Ancient Giant Ooids
Certificate(s): Applications of Computing, Statistics and Machine Learning, Sustainable Energy
I studied ooids, which are small, sedimentary grains that form in shallow water. Ooids grow through precipitation and shrink through abrasion, so their shapes and sizes vary greatly depending on environmental factors such as ocean chemistry and current velocity. Our goal was to construct three-dimensional models of ancient ooids in order to measure their morphology. These measurements provide insight into ocean conditions throughout Earth’s history, and help us better understand the ocean’s response to climate perturbations. I automated the process of creating 3D models by developing a machine learning algorithm that could independently detect ooids from an image. This process required lots of work removing noise from images, performing segmentations, and extracting shapes from the processed images. I gained substantial experience with the powerful MATLAB programming language by using it to develop all of my code. Moreover, I had the opportunity to work on an original research project that helped prepare me for future independent work at Princeton. This internship was an amazing opportunity and, as a result, I am now pursuing the statistics and machine learning certificate to pursue similar work in the future.
Climate and Environmental Science
Maloof Research Group, Department of Geosciences, Princeton University
Adam Maloof, Professor of Geosciences; Bolton Howes, Ph.D. candidate, Geosciences